CN117873765B

CN117873765B - Distributed acquisition data processing method and system

Info

Publication number: CN117873765B
Application number: CN202311783223.5A
Authority: CN
Inventors: 洪智; 刘雄
Original assignee: Jiangsu Dake Digital Intelligence Technology Co ltd
Current assignee: Jiangsu Dake Digital Intelligence Technology Co ltd
Priority date: 2023-12-22
Filing date: 2023-12-22
Publication date: 2024-05-28
Anticipated expiration: 2043-12-22
Also published as: CN117873765A

Abstract

The invention provides a distributed acquisition data processing method and system, which are used for receiving structure configuration information of a target user, generating a distributed monitoring structure according to the structure configuration information, wherein the distributed monitoring structure comprises an upper framework layer and a lower acquisition layer; determining a target checking group string according to a checking strategy, and acquiring checking equipment information corresponding to the target checking group string, wherein the checking equipment information comprises static equipment information and dynamic equipment information; acquiring a side image of the target checking group string based on static equipment information, calling a side angle processing strategy, and performing angle judgment on the side image to obtain a side judgment image; acquiring a top surface image of the target checking group string based on the dynamic equipment information, calling a top surface angle processing strategy, and performing angle judgment on the top surface image to obtain a top surface judgment image; and updating the acquisition layer according to the side face judgment image and/or the top face judgment image to obtain a distributed checking structure and sending the distributed checking structure to a checking end.

Description

Distributed acquisition data processing method and system

Technical Field

The present invention relates to data processing technologies, and in particular, to a distributed collected data processing method and system.

Background

The distributed data collection processing refers to a technology for collecting and simultaneously processing data distributed in each area on a large scale, so that the data of the same user can be monitored and processed in real time conveniently, for example, a photovoltaic enterprise has photovoltaic projects in each area, and therefore, the photovoltaic monitoring data of each area needs to be integrated, so that the user can intervene and manage in time conveniently.

In the prior art, the rotation angle of the photovoltaic panel can be automatically adjusted when the photovoltaic panel is installed, so that sunlight is received to the greatest extent, and the power generation efficiency is improved, however, due to the fact that the photovoltaic panel is influenced by factors such as environment, service life and the like, abnormal rotation and even incapability of rotating can be caused, the angle sensor is generally utilized to monitor the abnormal rotation, however, the angle sensor and the angle rotating mechanism are integrated and are easy to damage, so that a user cannot position the abnormal photovoltaic panel in time, and the power generation efficiency is lower.

Therefore, how to identify the data of the photovoltaic panel acquired in a distributed manner, so that an abnormal photovoltaic panel is positioned, and a user can intervene and repair in time, so that the power generation efficiency is improved, and the problem to be solved urgently is solved.

Disclosure of Invention

The embodiment of the invention provides a distributed acquisition data processing method and system, which can identify acquired photovoltaic panel data so as to position an abnormal photovoltaic panel, so that a user can intervene in repairing in time, and the power generation efficiency is improved.

In a first aspect of an embodiment of the present invention, a distributed collected data processing method is provided, including:

receiving structure configuration information of a target user, and generating a distributed monitoring structure according to the structure configuration information, wherein the distributed monitoring structure comprises an upper framework layer and a lower acquisition layer;

Determining a target verification group string according to a verification policy, and acquiring verification equipment information corresponding to the target verification group string, wherein the verification equipment information comprises static equipment information and dynamic equipment information;

acquiring a side image of the target checking group string based on the static equipment information, calling a side angle processing strategy, and performing angle judgment on the side image to obtain a side judgment image;

acquiring a top surface image of the target checking group string based on the dynamic equipment information, calling a top surface angle processing strategy, and performing angle judgment on the top surface image to obtain a top surface judgment image;

and updating the acquisition layer according to the side face judgment image and/or the top face judgment image to obtain a distributed checking structure and sending the distributed checking structure to a checking end.

Optionally, in a possible implementation manner of the first aspect, the receiving the configuration information of the target user, generating a distributed monitoring structure according to the configuration information, includes:

Receiving structure configuration information of a target user, wherein the structure configuration information comprises area information and group string information corresponding to the area information;

Constructing a management node corresponding to the target user, constructing an area node corresponding to the area information, and connecting the area node with the management node;

And constructing a string node corresponding to the string information, connecting the string node with a corresponding area node to generate a framework layer, and generating an acquisition layer below the framework layer to obtain a distributed monitoring structure.

Optionally, in one possible implementation manner of the first aspect, the determining, according to a verification policy, a target verification group string, and obtaining verification device information corresponding to the target verification group string includes:

Acquiring preset checking frequency and last historical checking time of each group of string information, and determining current checking frequency according to current time and the historical checking time;

And determining that the current checking frequency is equal to the preset checking frequency, taking the corresponding group string information as a target checking group string, and acquiring checking equipment information corresponding to the target checking group string, wherein the target checking group string comprises a plurality of target checking panels.

Optionally, in one possible implementation manner of the first aspect, the acquiring a side image of the target verification string based on the static device information, invoking a side angle processing policy, performing angle judgment on the side image, and obtaining a side judgment image includes:

Acquiring a side image of the target verification group string based on the static equipment information, and extracting adjacent pixel points in the side image according to a side pixel value to obtain a side pixel point set corresponding to each target verification panel;

Identifying the outline formed by the pixels in each side pixel set according to OpenCV, obtaining a side frame outline corresponding to the target checking panel, and extracting a side frame image corresponding to each side pixel set;

acquiring the center point of each side frame profile as a profile midpoint, and determining a central line passing through the profile midpoint and perpendicular to the length direction of the side frame profile;

2 intercepting lines are generated at the outline length direction of the side frame based on the central line and a preset intercepting distance, and the side frame image is intercepted based on the intercepting lines to obtain side detection images corresponding to the target checking panels;

And (3) retrieving a side angle processing strategy, and performing angle judgment on the side detection image to obtain a side judgment image.

Optionally, in one possible implementation manner of the first aspect, the retrieving a side angle processing policy, performing angle judgment on the side detection image to obtain a side judgment image, includes:

Selecting any one of the side detection images as a first detection image, and taking the rest of the side detection images as a second detection image;

Overlapping the first detection image and each second detection image according to the contour middle points, and calculating the overlapping duty ratio of each second detection image after overlapping;

Classifying the target inspection panels based on the overlapping duty ratio to obtain a first detection set and a second detection set;

Determining an anomaly detection set based on comparison results of the number of target check panels in the first detection set and the second detection set, and taking the target check panel corresponding to the anomaly detection set as a side anomaly panel;

and updating the side image according to the side abnormal panel to obtain a side judgment image.

Optionally, in a possible implementation manner of the first aspect, the classifying the target inspection panel based on the overlapping duty ratio to obtain a first detection set and a second detection set includes:

determining the largest overlapping duty ratio as a reference duty ratio, and determining the rest overlapping duty ratios as classification duty ratios;

Placing the target checking panel corresponding to the first detection image and the reference duty ratio in a first detection set;

Calculating according to the reference duty ratio and the classifying duty ratio to obtain a difference duty ratio;

and determining that the difference duty ratio is smaller than or equal to a preset duty ratio, classifying the target inspection panels corresponding to the classification duty ratio into the first detection set, and classifying the rest target inspection panels corresponding to the classification duty ratio into the second detection set.

Optionally, in one possible implementation manner of the first aspect, the acquiring a top image of the target verification string based on the dynamic device information, invoking a top angle processing policy, performing angle judgment on the top image, and obtaining a top judgment image includes:

Acquiring a top image of the target checking group string based on the dynamic equipment information, and extracting adjacent pixel points in the top image according to frame pixel values to obtain frame pixel point sets corresponding to each target checking panel;

Identifying the outline formed by the pixel points in each frame pixel point set according to OpenCV to obtain the top frame outline corresponding to the target checking panel;

Acquiring the number of pixel points in the outline of the top surface frame to obtain the angle identification number corresponding to the target checking panel;

Classifying the target checking panels based on the angle recognition quantity to obtain a first recognition set and a second recognition set;

Determining an abnormal recognition set based on comparison results of the number of target checking panels in the first recognition set and the second recognition set, and taking the target checking panel corresponding to the abnormal recognition set as a top surface abnormal panel;

and updating the top surface image according to the top surface abnormal panel to obtain a top surface judgment image.

Optionally, in a possible implementation manner of the first aspect, the classifying the target inspection panel based on the number of angle identifications to obtain a first identification set and a second identification set includes:

selecting any one angle identification number as a reference number, taking the rest angle identification numbers as classification numbers, and placing target check panels corresponding to the reference number in a first identification set;

calculating the difference quantity according to the reference quantity and the classifying quantity;

And determining that the difference quantity is smaller than or equal to a preset quantity, classifying the target checking panels corresponding to the classifying quantity into a first recognition set, and classifying the rest target checking panels corresponding to the classifying quantity into a second recognition set.

Optionally, in one possible implementation manner of the first aspect, the updating the acquisition layer according to the side judgment image and/or the top judgment image to obtain a distributed checking structure is sent to a checking end, and includes:

Acquiring image acquisition time corresponding to the side face judgment image and/or the top face judgment image, constructing a time node in the acquisition layer based on the image acquisition time, and binding the corresponding side face judgment image and/or the top face judgment image with the time node;

And determining corresponding group string nodes in the architecture layer as connection nodes based on the target checking group strings, connecting the time nodes with the connection nodes, obtaining a distributed checking structure and sending the distributed checking structure to a checking end.

In a second aspect of an embodiment of the present invention, there is provided a distributed acquisition data processing system, including:

The generation module is used for receiving the structure configuration information of the target user, and generating a distributed monitoring structure according to the structure configuration information, wherein the distributed monitoring structure comprises an upper framework layer and a lower acquisition layer;

the acquisition module is used for determining a target checking group string according to a checking strategy and acquiring checking equipment information corresponding to the target checking group string, wherein the checking equipment information comprises static equipment information and dynamic equipment information;

the side judgment module is used for acquiring a side image of the target checking group string based on the static equipment information, invoking a side angle processing strategy, and carrying out angle judgment on the side image to obtain a side judgment image;

The top surface judging module is used for acquiring a top surface image of the target checking group string based on the dynamic equipment information, invoking a top surface angle processing strategy, and carrying out angle judgment on the top surface image to obtain a top surface judging image;

And the updating module is used for updating the acquisition layer according to the side face judging image and/or the top face judging image, so as to obtain a distributed checking structure and send the distributed checking structure to a checking end.

The beneficial effects of the invention are as follows:

1. The invention can judge the angles of the side image and the top image of the target checking string, thereby obtaining the side judging image and the top judging image, facilitating the user to position the abnormal string information and the photovoltaic module, generating a distributed checking structure according to the side judging image and the top judging image, and facilitating the user to position and intervene the abnormal photovoltaic module in time. The invention constructs the distributed monitoring structure according to the structure configuration information, so that all string information managed by the corresponding user is acquired and angle identification is carried out on the images of the target checking string according to the static equipment information and the dynamic equipment information, thereby obtaining the photovoltaic panel with the side judgment image and the top judgment image helping the user to locate the abnormality, updating the distributed monitoring structure according to the side judgment image and/or the top judgment image, thereby obtaining the distributed checking structure, facilitating the user to locate the abnormal string information in time and the photovoltaic assembly to intervene and maintain in time, and improving the power generation efficiency.

2. The invention can construct a distributed monitoring structure so as to update the photovoltaic module according to the abnormality to obtain a distributed checking structure, thereby facilitating the subsequent user to position the abnormal photovoltaic module in time, the user can process the images of each group of strings according to the actual condition of the target checking group strings by adopting different strategies, thereby positioning the abnormal photovoltaic module, and update the distributed monitoring structure to obtain the distributed checking structure, so that the user can position the abnormal photovoltaic module in time through the distributed checking structure to maintain in time, thereby improving the power generation efficiency. The invention constructs the distributed supervision structure according to the region information and the corresponding group string information in the structure configuration information, all node layers between the group string nodes and the management nodes are fixed architecture layers, and the group string nodes in the architecture layers can update abnormal time nodes and abnormal nodes according to actual conditions, thereby obtaining the distributed checking structure and facilitating the positioning of users.

3. According to the invention, different strategies are adopted to process the images of each group of strings according to the actual condition of the target checking group string, so that the abnormal photovoltaic module is positioned. And when the static equipment information is judged to be provided, acquiring side images of the target checking group string, and overlapping one side image with the rest side images, so that the similarity of each image is obtained, and grouping is carried out according to the similarity, and the probability of damaging a plurality of components is extremely low for the group string information at the same time, so that the server can automatically select the abnormal photovoltaic components with less grouping quantity. According to the method, when the dynamic equipment information is judged, the number of the top surface pixel points of each photovoltaic module is directly obtained, the photovoltaic modules are grouped according to the number, and the photovoltaic modules with fewer numbers are selected to be used as abnormal photovoltaic modules, so that the abnormal photovoltaic modules are positioned, the branches at the abnormal nodes are highlighted later, the abnormal photovoltaic modules are positioned quickly when the checking terminal checks, and the experience of a user is improved.

Drawings

FIG. 1 is a flow chart of a distributed acquisition data processing method provided by the invention;

FIG. 2 is a schematic diagram of a distributed monitoring architecture according to the present invention;

FIG. 3 is a schematic diagram of a side detection image generation method according to the present invention;

FIG. 4 is a schematic diagram of an updated distributed monitoring architecture according to the present invention;

fig. 5 is a schematic structural diagram of a distributed acquisition data processing system according to the present invention.

Detailed Description

The technical scheme of the invention is described in detail below by specific examples. The following embodiments may be combined with each other, and some embodiments may not be repeated for the same or similar concepts or processes.

The invention provides a distributed acquisition data processing method, which is shown in figure 1 and comprises the following steps of S1-S5:

s1, receiving structure configuration information of a target user, and generating a distributed monitoring structure according to the structure configuration information, wherein the distributed monitoring structure comprises an upper framework layer and a lower acquisition layer.

It should be noted that, photovoltaic enterprises have photovoltaic projects in all areas, so that the photovoltaic monitoring data of all areas need to be integrated, and users can monitor and manage uniformly. Therefore, a distributed monitoring structure corresponding to the target user needs to be constructed, so that the user can conveniently perform unified management.

It will be appreciated that the server receives configuration information of the target user, wherein the configuration information is information configured to build the distributed monitoring structure.

Further, the server may generate a distributed monitoring structure according to the structure configuration information, where the distributed monitoring structure includes an upper architecture layer and a lower acquisition layer.

In some embodiments, the step S1 (receiving the configuration information of the target user, and generating the distributed monitoring structure according to the configuration information) includes S11-S13:

S11, receiving structure configuration information of a target user, wherein the structure configuration information comprises area information and group string information corresponding to the area information.

It can be understood that the server receives the configuration information of the target user, where the configuration information includes the area information and the group string information corresponding to the area information. The target user may be a photovoltaic business, such as business a.

It will be appreciated that the zone information may be photovoltaic zones managed by the target user, such as zones a and b. The string information may be a corresponding string of photovoltaic groups within each photovoltaic region, for example, region a has strings 1,2, and 3 and region b has strings 4, 5, and 6.

S12, constructing a management node corresponding to the target user, constructing an area node corresponding to the area information, and connecting the area node with the management node.

It can be understood that the server constructs corresponding area nodes according to the management nodes constructed by the target users and the area information, and connects all the area nodes with the management nodes.

For example, a management node a corresponding to the enterprise a is constructed, and corresponding area nodes a and b are constructed according to the areas a and b, and the area nodes a and b are connected with the management node a.

And S13, constructing a string node corresponding to the string information, connecting the string node with a corresponding region node to generate a framework layer, and generating an acquisition layer below the framework layer to obtain the distributed monitoring structure.

It can be understood that the server constructs a group string node corresponding to the group string information, connects the group string node with a corresponding area node to generate a framework layer, and generates an acquisition layer below the framework layer to obtain the distributed monitoring structure.

For example, as shown in fig. 2, string nodes corresponding to photovoltaic string 1 to 6 are constructed, string node 1-3 is connected with regional node a, string node 4-6 is connected with regional node b, so as to obtain an architecture layer, and a corresponding acquisition layer is generated below the architecture layer.

S2, determining a target checking group string according to a checking strategy, and acquiring checking equipment information corresponding to the target checking group string, wherein the checking equipment information comprises static equipment information and dynamic equipment information.

It should be noted that when the rotation angle of the photovoltaic panel is detected in real time in daily use, the angle sensor is used for detecting and judging, but in order to avoid abnormal rotation of the angle of the photovoltaic panel in the photovoltaic string caused by damage of the angle sensor and the angle rotation mechanism, the power generation efficiency is low, therefore, the system can be used for detecting at intervals, for example, once every 3 days, so as to ensure normal operation of the photovoltaic string.

It can be understood that the server determines the target verification group string according to the set verification policy, and obtains verification device information corresponding to the target verification group string, where the verification device information includes static device information and dynamic device information.

The target checking group string is a photovoltaic group string to be checked, the checking equipment information is checking equipment corresponding to the target checking group string, the checking equipment information comprises static equipment information and dynamic equipment information, for example, the static equipment information can be a fixed camera arranged on the side face of the photovoltaic group string, and the dynamic equipment information can be an unmanned aerial vehicle.

It should be noted that, because the area occupied by the photovoltaic area is wider, the complexity of environments where different photovoltaic strings are located in the area is different, and the number of photovoltaic panels in the photovoltaic strings is different, but part of the photovoltaic strings cannot be collected comprehensively, for example, the number of photovoltaic panels in the photovoltaic strings is more, for example, 20 photovoltaic panels are arranged in the photovoltaic strings, but the camera can only collect 10 photovoltaic panels, so that the collection is complete through the side camera, therefore, part of the photovoltaic strings are suitable for collecting through the side fixed cameras, and part of the photovoltaic strings cannot be monitored through the fixed cameras, but are collected through unified shooting by using the unmanned aerial vehicle.

For example, photovoltaic string 1 has a fixed camera and photovoltaic string 2 does not have a fixed camera.

In some embodiments, in step S2 (determining the target verification group string according to the verification policy, and obtaining verification device information corresponding to the target verification group string) includes S21-S22:

S21, acquiring preset checking frequency and last historical checking time of each group string information, and determining current checking frequency according to current time and the historical checking time.

It can be understood that the server may acquire the preset checking frequency and the last historical checking time of each group of string information, and determine the current checking frequency according to the current time and the historical checking time.

It will be appreciated that each string of photovoltaic modules has a corresponding preset checking frequency, for example 1 time 3 days, 1 minute 3, specifically set according to the environment and the degree of easy damage, and may be manually preset. According to the current time and the last historical checking time, for example, the current time of the photovoltaic string 1 is 8 months and 10 days, the last historical checking time is 8 months and 7 days, 3 days are obtained through calculation, the frequency is 1 of 3 minutes, the checking frequency of 1 time is just satisfied for 3 days, and the photovoltaic string 1 is taken as the target checking string in the follow-up. The historical checking time is the time of the last checking.

S22, determining that the current checking frequency is equal to the preset checking frequency, taking the corresponding group string information as a target checking group string, and obtaining checking equipment information corresponding to the target checking group string, wherein the target checking group string comprises a plurality of target checking panels.

It can be appreciated that the server determines that the current checking frequency is equal to the preset checking frequency, and takes the corresponding group string information as a target checking group string, for example, takes the photovoltaic group string 1 as the target checking group string.

Further, the information of the checking device corresponding to the target checking group string is obtained, for example, the information of the checking device corresponding to the target checking group string is obtained, and at this time, the target checking group string is the photovoltaic group string 1 and has a corresponding fixed camera. Wherein the target verification string comprises a plurality of target verification panels, it is easy to understand that the photovoltaic string has a plurality of photovoltaic panels.

S3, acquiring a side image of the target checking group string based on the static equipment information, invoking a side angle processing strategy, and performing angle judgment on the side image to obtain a side judgment image.

It can be appreciated that if the target verification string has corresponding static device information, a side image of the target verification string is obtained based on the static device information, wherein the side image is a side image of the target verification string.

Further, the server invokes a side angle processing strategy, performs angle judgment on the side frame image of each photovoltaic panel in the side images, and updates the side images based on the photovoltaic panel with abnormal angle when judging the photovoltaic panel with abnormal angle to obtain side judgment images.

In some embodiments, the step S3 (acquiring a side image of the target verification string based on the static device information, invoking a side angle processing policy, performing angle judgment on the side image, and obtaining a side judgment image) includes S31-S35:

S31, acquiring a side image of the target verification group string based on the static equipment information, and extracting adjacent pixel points in the side image according to the side pixel value to obtain a side pixel point set corresponding to each target verification panel.

It can be understood that the server may acquire the side image of the target verification group string based on static device information, and extract adjacent pixels in the side image according to the side pixel value, so as to obtain a side pixel set corresponding to each target verification panel.

Where the side pixel values are those of a photovoltaic panel frame, typically a photovoltaic panel is surrounded by a white frame, typically made of aluminum, for the primary purpose of providing protection and support while also improving the appearance and mounting of the panel. Therefore, the side pixel value can be white or other colors, and can be set according to actual conditions and manually preset.

It is to be understood that the side image corresponds to a side image of the photovoltaic string, and therefore, the side image has side frame images of a plurality of photovoltaic panels, and therefore, a plurality of side pixel point sets can be obtained by extracting adjacent pixel points according to side pixel values, and each side pixel point set corresponds to one target inspection panel.

S32, recognizing the outline formed by the pixels in each side surface pixel point set according to OpenCV, obtaining the side surface frame outline corresponding to the target checking panel, and extracting the side surface frame image corresponding to each side surface pixel point set.

It should be noted that OpenCV is a powerful computer vision library that can be used to identify and process objects and features in various images and videos, such as face recognition, object recognition, and contour recognition.

It can be understood that the server identifies the outline formed by the pixels in each side pixel set according to OpenCV, so as to obtain the outline of the side frame corresponding to the target checking panel. The prior art is not described herein in detail.

Further, a side frame image corresponding to each side pixel point set is determined, for example, the side frame image corresponding to each side pixel point set is obtained by intercepting the side frame image by using all the pixel points in each side pixel point set. It is to be understood that, at this time, a white rectangular frame image of the side face of each photovoltaic panel is obtained, and the position of each target inspection panel in the side face image obtained by photographing the target inspection group string by the camera is fixed, so that the side face frame image corresponding to the target inspection panel can be determined.

S33, acquiring the center point of each side frame profile as a profile midpoint, and determining a central line which passes through the profile midpoint and is perpendicular to the length direction of the side frame profile.

It will be appreciated that the server may obtain the center point of the side frame outline as the outline midpoint, e.g., determine the center point of the rectangle as the outline midpoint.

Further, the server will determine a midline through the midpoint of the contour and perpendicular to the length of the side frame contour.

S34, 2 intercepting lines are generated at the length direction of the profile of the side frame based on the central line and the preset intercepting distance, and the side frame image is intercepted based on the intercepting lines, so that side detection images corresponding to the target checking panels are obtained.

It can be understood that, as shown in fig. 3, the server generates 2 intercepting lines at the profile length direction of the side frame based on the central line and the preset intercepting distance, and intercepts the side frame image according to the 2 intercepting lines to obtain side detection images corresponding to each target inspection panel.

Through the embodiment, the partial image in the middle of the corresponding side frame image of each target checking panel can be obtained, and subsequent angle comparison is carried out, so that the data processing amount is reduced.

And S35, a side face angle processing strategy is called, and angle judgment is carried out on the side face detection image, so that a side face judgment image is obtained.

It can be understood that the server may invoke a side angle processing policy to perform angle judgment on the side detection image, so as to obtain a side judgment image.

In some embodiments, the step S35 (retrieving a side angle processing policy, performing angle judgment on the side detection image to obtain a side judgment image) includes S351-S355:

s351, selecting any one of the side detection images as a first detection image, and taking the rest of the side detection images as a second detection image.

It will be appreciated that the server may select any one of the side detection images as the first detection image and use the remaining side detection images as the second detection image.

And S352, overlapping the first detection image and each second detection image according to the contour middle points, and calculating the overlapping duty ratio of each second detection image after overlapping.

It can be understood that the server sequentially overlaps the first detection image and each second detection image according to the contour midpoint, and it is easy to understand that if all the photovoltaic panels in the photovoltaic string rotate without abnormality, that is, the rotation angles are the same, the corresponding overlapping after overlapping is relatively high, for example, 98%, 99% or the like. If an abnormal panel occurs, the overlapping duty ratio may deviate greatly.

And S353, classifying the target checking panel based on the overlapping duty ratio to obtain a first detection set and a second detection set.

It should be noted that, the photovoltaic string is formed by connecting a plurality of photovoltaic panels in series, and the probability of occurrence of a plurality of damages is extremely low.

Therefore, the server classifies the target inspection panels based on the overlapping occupation ratios, and classifies the overlapping occupation ratios into a set approximately, thereby obtaining a first detection set and a second detection set.

By the above embodiment, it is possible to determine the set as the abnormality in which the number of target verification panels is small in the first detection set and the second detection set.

In some embodiments, in step S353 (classifying the target inspection panel based on the overlapping duty ratio to obtain a first detection set and a second detection set) includes S3531-S3534:

And S3531, determining the largest overlapping duty ratio as a reference duty ratio, and determining the rest overlapping duty ratios as classification duty ratios.

It will be appreciated that the server will determine the maximum overlap ratio as the reference ratio, i.e., the overlap ratio of the target inspection panel closest to the first detected image angle as the reference ratio. And the remaining overlap duty cycle is determined as the classification duty cycle.

For example, the overlapping ratio is 98%, 20%, 99% and 100% in order, 100% is selected as the reference ratio, and the other 98%, 20% and 99% are classified ratios.

And S3532, placing the target checking panel corresponding to the first detection image and the reference duty ratio in a first detection set.

It is understood that the target inspection panels corresponding to the first detection image and the reference duty ratio are placed in the first detection set, and it is not difficult to understand that the target inspection panels corresponding to the reference duty ratio overlap the target inspection panels of the first detection image to the maximum duty ratio, so that 2 are classified into one set.

And S3533, calculating according to the reference duty ratio and the classifying duty ratio to obtain a difference duty ratio.

It will be appreciated that the difference duty cycle is derived from the absolute value of the difference between the reference duty cycle and the classification duty cycle.

For example, 100% is differentiated from the classification ratios 98%, 20%, 99% in order, resulting in 2%, 80%, 1%.

S3534, determining that the difference duty ratio is smaller than or equal to a preset duty ratio, classifying the target check panels corresponding to the classification duty ratio into the first detection set, and classifying the rest target check panels corresponding to the classification duty ratio into the second detection set.

It can be understood that the server determines that the difference duty ratio is smaller than or equal to a preset duty ratio, and classifies the target inspection panel corresponding to the classification duty ratio into the first detection set. The preset duty cycle may be an artificially preset duty cycle, for example, 5%.

For example, 2%, 80%, and 1% are less than 5%, and the target inspection panels corresponding to the classification ratios of 2% and 1% are classified into the first detection set, and the target inspection panels corresponding to the classification ratios of 20% are classified into the second detection set.

S354, determining an anomaly detection set based on the comparison result of the number of the target check panels in the first detection set and the second detection set, and taking the target check panel corresponding to the anomaly detection set as a side anomaly panel.

It can be understood that, according to the comparison result of the number of the target checking panels in the first detection set and the second detection set, the set with the least number is determined as the anomaly detection set, and the target checking panel in the anomaly detection set is taken as the side anomaly panel.

For example, there are only 1 target inspection panels in the second inspection set, and there are 4 target inspection panels in the second inspection set, so the target inspection panels in the second inspection set are all rotation abnormal, i.e., the least number of photovoltaic panels in the set are selected as rotation abnormal.

And S355, updating the side image according to the side abnormal panel to obtain a side judgment image.

It can be understood that the server updates the side image according to the side abnormal panel to obtain a side judgment image.

For example, if the second detection set is a photovoltaic panel corresponding to the number 03, a side frame image corresponding to the photovoltaic panel corresponding to the number 03 in the side image is determined, and the side frame image is highlighted, for example, may be marked red, so as to obtain a side judgment image.

S4, acquiring a top surface image of the target checking group string based on the dynamic equipment information, invoking a top surface angle processing strategy, and performing angle judgment on the top surface image to obtain a top surface judgment image.

It should be noted that, if a part of the photovoltaic strings do not have a corresponding fixed camera, then the unmanned aerial vehicle can shoot at a preset point location, each photovoltaic string has a set point location, and a top surface image corresponding to the photovoltaic string is acquired.

It can be understood that the server may acquire the top image of the target verification string based on the dynamic device information, invoke a top angle processing policy, and perform angle judgment on the top image to obtain a top judgment image. Wherein the top image is the top image of the target verification group string.

In some embodiments, step S4 (obtaining a top image of the target verification string based on the dynamic device information, invoking a top angle processing policy, performing angle judgment on the top image, and obtaining a top judgment image) includes S41-S46:

S41, acquiring a top image of the target checking group string based on the dynamic equipment information, and extracting adjacent pixel points in the top image according to the frame pixel values to obtain a frame pixel point set corresponding to each target checking panel.

It should be noted that the photovoltaic string is obtained by connecting a plurality of photovoltaic panels in series, and each photovoltaic panel is provided with a corresponding white frame for wrapping, so that the installation is convenient.

It can be understood that the server may obtain the top image of the target verification group string based on the dynamic device information, and extract the adjacent pixel points in the top image according to the frame pixel values, so as to obtain a frame pixel point set corresponding to each target verification panel.

The border pixel value is a border frame pixel value corresponding to each target inspection panel, for example, may be white.

S42, identifying the outline formed by the pixel points in each frame pixel point set according to OpenCV to obtain the top frame outline corresponding to the target checking panel.

It can be understood that the outline formed by the pixels in each frame pixel set is identified through OpenCV, so as to obtain the outline of the top frame corresponding to the target checking panel.

It is to be understood that when the unmanned aerial vehicle shoots the photovoltaic panels in a overlooking manner, the rotation angles are different, and the number of pixel points displayed by each photovoltaic panel in the top surface image is different correspondingly, for example, the panel is 180 degrees when the noon is vertical illumination, and the number of pixel points displayed by each photovoltaic panel in the top surface image is the largest, and the number of pixel points gradually decreases after rotation. The number of pixels can then be used to determine whether a rotating anomaly in the photovoltaic panel has occurred.

S43, obtaining the number of the pixel points in the outline of the top surface frame, and obtaining the angle identification number corresponding to the target checking panel.

It can be understood that the server obtains the number of pixels inside the outline of the top surface frame, that is, the number of pixels inside the frame of each target checking panel, so as to obtain the number of angle identifications corresponding to the target checking panels. The greater the number of angular identifications, the greater the area that the corresponding photovoltaic panel exhibits in the top image.

And S44, classifying the target checking panels based on the angle recognition quantity to obtain a first recognition set and a second recognition set.

It can be appreciated that the server classifies the target verification panels based on the number of angle identifications, resulting in a first identification set and a second identification set.

In some embodiments, in step S44 (classifying the target inspection panel based on the angle recognition number to obtain a first recognition set and a second recognition set), S441-S443:

s441, selecting any one of the angle identification numbers as a reference number, taking the rest of the angle identification numbers as a classification number, and placing the target checking panel corresponding to the reference number in a first identification set.

It should be noted that, with a plurality of photovoltaic panels in the photovoltaic string, 1 or several damage will generally occur, and compared with the whole photovoltaic string, all photovoltaic panels occupy less area, and the probability of damage is very low.

Therefore, the server selects any one of the angle identification numbers as a reference number, takes the rest of the angle identification numbers as a classification number, and places the target verification panel corresponding to the reference number in the first identification set.

S442, calculating the difference quantity according to the reference quantity and the classifying quantity.

It will be appreciated that the number of differences is derived from the absolute value of the difference between the reference number and the categorized number.

For example, the reference number is 100, the classification number is 98, 20, 90, and the difference number is 2, 80, 10.

S443, determining that the difference quantity is smaller than or equal to a preset quantity, classifying the target check panels corresponding to the classifying quantity into a first recognition set, and classifying the rest target check panels corresponding to the classifying quantity into a second recognition set.

It can be understood that the number of the differences is determined to be less than or equal to a preset number, the target inspection panels corresponding to the corresponding classifying number are classified into a first recognition set, and the rest of the target inspection panels corresponding to the classifying number are classified into a second recognition set. The preset number is artificially preset, and is specifically set according to actual conditions.

For example, if the preset number is 50,2, and 10 are less than 50, the target inspection panels corresponding to 98 and 90 are classified into the first recognition set, and the target inspection panel corresponding to 20 is classified into the second recognition set.

S45, determining an abnormal recognition set based on the comparison result of the number of the target checking panels in the first recognition set and the second recognition set, and taking the target checking panel corresponding to the abnormal recognition set as a top surface abnormal panel.

It can be understood that the server may determine the abnormal recognition set based on the comparison result of the number of the target verification panels in the first recognition set and the second recognition set, that is, after the number comparison is performed, determine the first recognition set or the second recognition set with the minimum number as the abnormal recognition set, and use the target verification panel corresponding to the abnormal recognition set as the top surface abnormal panel.

For example, the first identification set has photovoltaic panels corresponding to 100, 98, 90, while the second identification set has only 20 photovoltaic panels as top surface anomaly panels.

And S46, updating the top surface image according to the top surface abnormal panel to obtain a top surface judgment image.

It will be appreciated that, consistent with the principle of step S355, the server updates the top image according to the top anomaly panel to obtain a top judgment image. That is, the image of the top surface abnormal panel in the top surface image is determined and highlighted, for example, the pixel value of the pixel point inside the corresponding top surface frame outline may be changed to red.

It is not difficult to understand that when unmanned aerial vehicle gathered the top surface image, can detect the luminance value of each photovoltaic panel in the photovoltaic group cluster, judge whether have more dust, whether in time clear up.

On the basis of the above embodiment, the method further comprises:

And acquiring panel brightness values of all target checking panels in the target checking group string, and taking the corresponding target checking panel as a panel to be cleaned when judging that the panel brightness values are smaller than preset brightness values.

It will be appreciated that a lower brightness value indicates more dust, and therefore requires cleaning by personnel, and the panel to be cleaned is sent to the inspection end. The preset brightness value is a human preset brightness value.

And sending the panel to be cleaned to a checking end.

And S5, updating the acquisition layer according to the side face judgment image and/or the top face judgment image, obtaining a distributed checking structure and sending the distributed checking structure to a checking end.

It can be understood that after the side face judgment image and/or the top face judgment image are obtained, updating is performed according to the acquisition layer, and the obtained distributed checking structure is sent to the checking end.

It is easy to understand that when the rotation of the photovoltaic panel in the photovoltaic string is abnormal, a corresponding time node is generated according to the abnormal time to update the acquisition layer, and the acquisition layer is a structural layer for recording the abnormal occurrence of the acquisition data.

In some embodiments, in step S5 (updating the acquisition layer according to the side judgment image and/or the top judgment image to obtain a distributed check structure, and sending the distributed check structure to a checking end), the method includes S51-S52:

S51, acquiring image acquisition time corresponding to the side face judgment image and/or the top face judgment image, constructing a time node in the acquisition layer based on the image acquisition time, and binding the corresponding side face judgment image and/or the top face judgment image with the time node.

It can be understood that the server may acquire an image acquisition time corresponding to the side judgment image and/or the top judgment image, construct a time node at the acquisition layer based on the image acquisition time, and bind the corresponding side judgment image and/or the top judgment image with the time node.

It is easy to understand that when the angular rotation abnormality is determined, corresponding acquisition time is established, a time node is constructed in the acquisition layer according to the acquisition time, and an abnormal side face judgment image and/or the top face judgment image is bound with the time node, so that the observation of a subsequent user is facilitated.

S52, determining corresponding group string nodes in the architecture layer as connection nodes based on the target checking group string, connecting the time nodes with the connection nodes, obtaining a distributed checking structure and sending the distributed checking structure to a checking end.

It can be understood that the server determines, based on the target checking group string, a corresponding group string node in the architecture layer as a connection node, that is, determines, as the connection node, a group string node corresponding to the target checking group string with an abnormality, and then connects the corresponding time node with the connection node, so as to obtain a distributed checking structure, and sends the distributed checking structure to the checking end.

For example, as shown in fig. 4, when the acquisition time of the side face judgment image corresponding to the photovoltaic string 1 is 8 months and 10 days, a time node corresponding to 8 months and 10 days is constructed, and the time node is connected with the string node1, so that the side face judgment image is bound with the string node 1.

Through the embodiment, the distributed checking structure can be generated to manage all the photovoltaic group strings simultaneously, and the photovoltaic group strings with abnormal conditions can be monitored and maintained conveniently in real time.

In order to better implement the distributed acquired data processing method provided by the present invention, the present invention further provides a distributed acquired data processing system, as shown in fig. 5, including:

The present invention also provides a readable storage medium having stored therein a computer program for implementing the methods provided by the various embodiments described above when executed by a processor.

The readable storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media can be any available media that can be accessed by a general purpose or special purpose computer. For example, a readable storage medium is coupled to the processor such that the processor can read information from, and write information to, the readable storage medium. In the alternative, the readable storage medium may be integral to the processor. The processor and the readable storage medium may reside in an Application SPECIFIC INTEGRATED Circuits (ASIC). In addition, the ASIC may reside in a user device. The processor and the readable storage medium may reside as discrete components in a communication device. The readable storage medium may be read-only memory (ROM), random-access memory (RAM), CD-ROMs, magnetic tape, floppy disk, optical data storage device, etc.

The present invention also provides a program product comprising execution instructions stored in a readable storage medium. The at least one processor of the device may read the execution instructions from the readable storage medium, the execution instructions being executed by the at least one processor to cause the device to implement the methods provided by the various embodiments described above.

In the above embodiment of the apparatus, it should be understood that the Processor may be a central processing unit (english: central Processing Unit, abbreviated as CPU), but may also be other general purpose processors, digital signal processors (english: DIGITAL SIGNAL Processor, abbreviated as DSP), application specific integrated circuits (english: application SPECIFIC INTEGRATED Circuit, abbreviated as ASIC), and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor for execution, or in a combination of hardware and software modules in a processor for execution.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims

1. A distributed acquisition data processing method, comprising:

Updating the acquisition layer according to the side face judgment image and/or the top face judgment image to obtain a distributed checking structure and sending the distributed checking structure to a checking end;

The receiving the structure configuration information of the target user, generating a distributed monitoring structure according to the structure configuration information, includes:

constructing a string node corresponding to the string information, connecting the string node with a corresponding area node to generate a framework layer, and generating an acquisition layer below the framework layer to obtain a distributed monitoring structure;

The determining the target checking group string according to the checking strategy, and obtaining the checking equipment information corresponding to the target checking group string, includes:

determining that the current checking frequency is equal to the preset checking frequency, taking the corresponding group string information as a target checking group string, and obtaining checking equipment information corresponding to the target checking group string, wherein the target checking group string comprises a plurality of target checking panels;

Acquiring a side image of the target checking group string based on the static equipment information, invoking a side angle processing strategy, performing angle judgment on the side image to obtain a side judgment image, and comprising the following steps:

A side face angle processing strategy is called, and angle judgment is carried out on the side face detection image to obtain a side face judgment image;

the step of retrieving a side angle processing strategy, performing angle judgment on the side detection image to obtain a side judgment image, includes:

Updating the side image according to the side abnormal panel to obtain a side judgment image;

The step of obtaining the top surface image of the target checking group string based on the dynamic equipment information, the step of calling a top surface angle processing strategy, and the step of performing angle judgment on the top surface image to obtain a top surface judgment image comprises the following steps:

2. The method of claim 1, wherein the step of determining the position of the substrate comprises,

Classifying the target inspection panel based on the overlapping duty ratio to obtain a first detection set and a second detection set, including:

3. The method of claim 1, wherein the step of determining the position of the substrate comprises,

Classifying the target inspection panel based on the angle identification number to obtain a first identification set and a second identification set, wherein the method comprises the following steps:

4. The method of claim 1, wherein the step of determining the position of the substrate comprises,

The step of updating the acquisition layer according to the side judgment image and/or the top judgment image to obtain a distributed checking structure and sending the distributed checking structure to a checking end comprises the following steps:

5. A distributed acquisition data processing system, comprising:

The updating module is used for updating the acquisition layer according to the side face judgment image and/or the top face judgment image, so as to obtain a distributed checking structure and send the distributed checking structure to a checking end;